Systems and methods for scanning data processing

ABSTRACT

The systems and method for processing scanning data of a scanning object are provided. The method may include acquiring, in a scanning process, at least two target phases of a motion of the scanning object, wherein the scanning process involves multiple data acquisition time points each of which corresponds to a scanning data set; identifying at least two first time periods during the scanning process, each first time period corresponding to one of the two target phases; determining a second time period that encloses the at least two first time periods; and retrieving once, from the multiple scanning data sets, second scanning data sets for reconstructing phase images each of which corresponds to one target phase, the second scanning data sets being acquired at second data acquisition time points of the multiple data acquisition time points within the second time period.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/998,009 filed on Aug. 20, 2020, which claims priority to ChinesePatent Application No. 201910770712.4, filed Aug. 20, 2019, the contentsof which are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to data processing, and inparticular, to systems and methods for processing scanning data.

BACKGROUND

Computed Tomography (CT) has emerged as a key imaging modality in thevisualization of anatomy. A CT device typically includes a radiationsource to project precisely collimated radiation beams (e.g., X-rays,gamma rays, etc.) through an object (e.g., a patient) being imaged, anda highly sensitive detector to detect the radiation beams passingthrough the object. The detected radiation beams can then be used forimage reconstruction.

At present, prospective image reconstruction of organs and/or tissues(e.g., the heart, the lung, etc.) of an object is mostly used inmulti-slice CT scans, especially with ultra-high-slice CT scans (such as128 slices). Generally, since the prospective image reconstruction canbe affected by physiological movements of the object, for example, forcardiac image reconstruction, the physiological movements caused byarrhythmia, tachycardia, etc. As a result, multiple images of differentmotion phases (or referred to as phase for brevity) may be reconstructedso that a doctor can select the reconstructed image with better imagequality for diagnosing the object. Therefore, it is desirable to providesystems and methods for multi-phase image reconstruction to improve theefficiency in the multi-phase image reconstruction.

SUMMARY

According to a first aspect of the present disclosure, a system isprovided. The system may include at least one storage device storingexecutable instructions for processing scanning data of a scanningobject generated during a scanning process, and at least one processorin communication with the at least one storage device, wherein whenexecuting the executable instructions, the at least one processor mayconfigured to cause the system to perform operations. The operations mayinclude acquiring, in a scanning process, at least two target phases ofa motion of a scanning object, wherein the scanning process involvesmultiple data acquisition time points each of which corresponds to ascanning data set; identifying at least two first time periods duringthe scanning process, each of the at least two first time periodscorresponding to one of the two target phases; determining a second timeperiod that encloses the at least two first time periods; and retrievingonce, from the multiple scanning data sets, second scanning data setsfor reconstructing phase images each of which corresponds to one of theat least two target phases, the second scanning data sets being acquiredat second data acquisition time points of the multiple data acquisitiontime points within the second time period.

In some embodiments, to identify the at least two first time periods,the operations may include identifying a starting time point and anending time point of a motion cycle of the motion; for each of the atleast two target phases, identifying, based on the target phase, thestarting time point of the motion cycle, and the ending time point ofthe motion cycle, a preset time point corresponding to the target phase;determining, based on the preset time point, a target data acquisitiontime point corresponding to the target phase; and determining, based onthe target data acquisition time point, the first period correspondingto the target phase.

In some embodiments the determining, based on the preset time point, atarget data acquisition time point corresponding to the target phase mayinclude determining whether there is a data acquisition time point amongthe multiple data acquisition time points that coincides with the presettime point corresponding to the target phase; in response to determiningthat there is a data acquisition time point among the multiple dataacquisition time points that coincides with the preset time point,designating the data acquisition time point as the target dataacquisition time point corresponding to the target phase; in response todetermining that there is no data acquisition time point among themultiple data acquisition time points that coincides with the presettime point, determining a difference between the preset time point andeach of the multiple data acquisition time points; identifying, amongthe multiple differences, a minimum difference; and designating the dataacquisition time point corresponding to the minimum difference as thetarget data acquisition time point corresponding to the target phase.

In some embodiments the at least two first time periods may both fallwithin a range within the motion cycle.

In some embodiments, the range may include a portion or all of themotion cycle.

In some embodiments, the determining, based on the target dataacquisition time point, the first time period corresponding to thetarget phase may include determining a target data acquisition angle atthe target data acquisition time point corresponding to the targetphase; determining a first angle range centering at the target dataacquisition angle corresponding to the target phase; and designating, asthe first time period, a plurality of data acquisition time points eachof which corresponds to a data acquisition angle within the first anglerange.

In some embodiments, the determining a second time period that enclosesthe at least two first time periods may include identifying a startingtime point and an ending time point for each of the at least two firsttime periods; designating an earlier starting time point of the at leasttwo starting time points of the at least two first time periods as astarting time point of the second time period; and designating a laterending time point of the at least two ending time points of the at leasttwo first time periods as an ending time point of the second timeperiod.

In some embodiments, the reconstructing phase images each of whichcorresponds to one of the at least two target phases may includepre-processing once the second scanning data sets; and generating, basedon the pre-processed second scanning data sets, the phase images.

In some embodiments, the generating, based on the pre-processed secondscanning data sets, the phase images may include for each of the atleast two target phases, identifying, from the pre-processed secondscanning data sets, pre-processed second scanning data sets of thetarget phase; and reconstructing, based on the pre-processed secondscanning data sets corresponding to the target phase, a phase image ofthe target phase.

In some embodiments, each of the pre-processed second scanning data setsof the target phase may correspond to a data acquisition angle, and thedata acquisition angles of the pre-processed second scanning data setsof the target phase may be with a first angle range corresponding to thetarget phase.

According to another aspect of the present disclosure, a method forprocessing scanning data may include one or more of the followingoperations. The method may include acquiring, in a scanning process, atleast two target phases of a motion of a scanning object, wherein thescanning process involves multiple data acquisition time points each ofwhich corresponds to a scanning data set; identifying at least two firsttime periods during the scanning process, each of the at least two firsttime periods corresponding to one of the two target phases; determininga second time period that encloses the at least two first time periods;and retrieving once, from the multiple scanning data sets, secondscanning data sets for reconstructing phase images each of whichcorresponds to one of the at least two target phases, the secondscanning data sets being acquired at second data acquisition time pointsof the multiple data acquisition time points within the second timeperiod.

According to yet another aspect of the present disclosure, anon-transitory computer readable medium is provided. The non-transitorycomputer readable medium may comprise at least one set of instructionsfor scanning data processing, wherein when executed by one or moreprocessors of a computing device, the at least one set of instructionsmay cause the computing device to perform a method. The method mayinclude acquiring, in a scanning process, at least two target phases ofa motion of a scanning object, wherein the scanning process involvesmultiple data acquisition time points each of which corresponds to ascanning data set; identifying at least two first time periods duringthe scanning process, each of the at least two first time periodscorresponding to one of the two target phases; determining a second timeperiod that encloses the at least two first time periods; and retrievingonce, from the multiple scanning data sets, second scanning data setsfor reconstructing phase images each of which corresponds to one of theat least two target phases, the second scanning data sets being acquiredat second data acquisition time points of the multiple data acquisitiontime points within the second time period.

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities, andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary data processingsystem according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware componentsand/or software components of an exemplary computing device according tosome embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware componentsand/or software components of an exemplary mobile device according tosome embodiments of the present disclosure;

FIG. 4 is a flowchart illustrating an exemplary process for processingscanning data of a scanning object during a scanning process accordingto some embodiments of the present disclosure;

FIG. 5 is a schematic flowchart illustrating an exemplary process fordetermining a second time period according to some embodiments of thepresent disclosure;

FIG. 6 is a schematic flowchart illustrating an exemplary process fordetermining a target data acquisition time point corresponding to atarget phase associated with a scanning process according to someembodiments of the present disclosure;

FIG. 7 is a schematic flowchart illustrating an exemplary process forreconstructing multiple-phase images of a scanning object according tosome embodiments of the present disclosure;

FIG. 8 is a block diagram of an exemplary processing device according tosome embodiments of the present disclosure;

FIG. 9A is a diagram illustrating an exemplary process for acquiringmultiple scanning data sets during a scanning process according to someembodiments of the present disclosure;

FIG. 9B is a diagram illustrating an exemplary process for determining afirst time period according to some embodiments of the presentdisclosure;

FIG. 9C is a diagram illustrating an exemplary process for determining asecond time period during a motion cycle (e.g., [RTag1, RTag2]) of amotion of a scanning object according to some embodiments of the presentdisclosure; and

FIG. 10 is a flowchart illustrating an exemplary single-phase imagereconstruction mode according to some embodiments of the presentdisclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant disclosure. However, it should be apparent to those skilledin the art that the present disclosure may be practiced without suchdetails. In other instances, well-known methods, procedures, systems,components, and/or circuitry have been described at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present disclosure. Various modifications to thedisclosed embodiments will be readily apparent to those skilled in theart, and the general principles defined herein may be applied to otherembodiments and applications without departing from the spirit and scopeof the present disclosure. Thus, the present disclosure is not limitedto the embodiments shown, but to be accorded the widest scope consistentwith the claims.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It will be understood that the term “system,” “unit,” “module,” and/or“block” used herein are one method to distinguish different components,elements, parts, sections, or assembly of different levels in ascendingorder. However, the terms may be displaced by another expression if theyachieve the same purpose.

Generally, the word “module,” “unit,” or “block,” as used herein, refersto logic embodied in hardware or firmware, or to a collection ofsoftware instructions. A module, a unit, or a block described herein maybe implemented as software and/or hardware and may be stored in any typeof non-transitory computer-readable medium or another storage device. Insome embodiments, a software module/unit/block may be compiled andlinked into an executable program. It will be appreciated that softwaremodules can be callable from other modules/units/blocks or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules/units/blocks configured for execution oncomputing devices (e.g., processor 310 as illustrated in FIG. 3 ) may beprovided on a computer readable medium, such as a compact disc, adigital video disc, a flash drive, a magnetic disc, or any othertangible medium, or as a digital download (and can be originally storedin a compressed or installable format that needs installation,decompression, or decryption prior to execution). Such software code maybe stored, partially or fully, on a storage device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules/units/blocks may be includedof connected logic components, such as gates and flip-flops, and/or canbe included of programmable units, such as programmable gate arrays orprocessors. The modules/units/blocks or computing device functionalitydescribed herein may be implemented as software modules/units/blocks,but may be represented in hardware or firmware. In general, themodules/units/blocks described herein refer to logicalmodules/units/blocks that may be combined with othermodules/units/blocks or divided into sub-modules/sub-units/sub-blocksdespite their physical organization or storage.

It will be understood that when a unit, engine, module or block isreferred to as being “on,” “connected to,” or “coupled to,” anotherunit, engine, module, or block, it may be directly on, connected orcoupled to, or communicate with the other unit, engine, module, orblock, or an intervening unit, engine, module, or block may be present,unless the context clearly indicates otherwise. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of this disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

The present disclosure provides mechanisms (which can include methods,systems, a computer-readable medium, etc.) for processing scanning dataof a scanning object generated during a scanning process. The method mayinclude acquiring, in the scanning process, at least two target phasesof a motion of a scanning object, wherein the scanning process involvesmultiple data acquisition time points each of which corresponds to ascanning data set. The method may further include identifying at leasttwo first time periods during the scanning process, each of the at leasttwo first time periods corresponding to one of the two target phases.The method may further include determining a second time period thatencloses the at least two first time periods. The method may furtherinclude retrieving once, from the multiple scanning data sets, secondscanning data sets for reconstructing phase images each of whichcorresponds to one of the at least two target phases, the secondscanning data sets being acquired at second data acquisition time pointsof the multiple data acquisition time points within the second timeperiod.

Generally, a single-phase image reconstruction mode (e.g., imagereconstruction of CT scan) may include selection of reconstruction data(or scanning data), retrieving of reconstruction data, pre-processing ofreconstruction data, image reconstruction, image fusion, post-processingof reconstructed images, etc., as illustrated in FIG. 10 . In someembodiments, since an image reconstruction process may be affected bymany factors, it is desired to reconstruct images of multiple phases (orreferred to as phase images) so that a user (e.g., a doctor) can selectbetter quality images for disease diagnosis. When images of multiplephases are to be reconstructed, some scanning data may correspond tomore than one phase that overlap. If the single-phase reconstructionmode is adopted, a series of processes, such as scanning data retrieval,preprocessing, post-processing, and reconstruction of reconstructiondata need to be performed for each phase. At least a portion of theoperations constitutes duplicate efforts with respect to scanning datacorresponding to overlapping phases. Therefore, by retrieving and/orpre-processing image data corresponding to multiple target phasestogether, repeated data retrieval and/or pre-precoessing can be avoided,thereby reducing the amount of computation resources, and improving theefficiency of the process for reconstructing images of multiple phasesand overall system performance.

FIG. 1 is a schematic diagram illustrating an exemplary data processingsystem according to some embodiments of the present disclosure.

As shown in FIG. 1 , the data processing system 100 may include ascanning device 110, a network 120, a terminal device 130, a processingdevice 140, and a storage device 150. In some embodiments, two or morecomponents of the data processing system 100 may be connected to and/orcommunicate with each other via a wireless connection (e.g., the network120), a wired connection, or a combination thereof. The components ofthe data processing system 100 may be connected in various ways. Merelyby way of example, the scanning device 110 may be connected to theprocessing device 140 through the network 120 or directly. As anotherexample, the storage device 150 may be connected to the processingdevice 140 through the network 120 or directly.

The scanning device 110 may include a single modality imaging deviceand/or a multi-modality imaging device, for example, a computedtomography (CT) device, a radiotherapy (RT) device, an image-guidedradiotherapy (IGRT), a computed tomography-magnetic resonance imaging(MRI-CT) device, an ultrasound inspection device, an X-ray photographydevice, etc. For illustration purposes, the CT device may be taken as anexemplary example of the scanning device 110.

The scanning device 110 may include a gantry 111, one or more detectors112, a detection region 113, a table 114, and a radiation source 115.The gantry 111 may be configured to provide support for other components(e.g., the detector(s) 112 and the radiation source 115, etc.) of thedata processing system 100. In some embodiments, the detector(s) 112 andthe radiation source 115 may be oppositely mounted on the gantry 111. Insome embodiments, the gantry 111 may rotate, for example, clockwise orcounterclockwise about an axis of rotation of the gantry 111. Thedetector(s) 112 and the radiation source 115 may rotate along with therotation of the gantry 111. The table 114 may be configured to locateand/or support a scanned object. A scanned object may be placed on thetable 114 and moved into the detection region 113 (e.g., a space betweenthe detector(s) 112 and the radiation source 115) of the scanning device110. The radiation source 115 may emit a beam of radiation to thescanned subject. The detector(s) 112 may be configured to detect theradiation beam (e.g., gamma photons) emitted from the detection region113. The detector(s) 112 may convert the radiation beam passing throughthe scanned object into the electrical signal, and then convert theelectrical signal into digital information by an analog/digitalconverter. The digital information may be inputted into the processingdevice for processing, or transmitted to the storage device 150 forstorage. In some embodiments, the detector(s) 112 may include one ormore detection units. The detector units may include a scintillationdetector (e.g., a cesium iodide detector) and/or other detectors. Thedetector units may be and/or include a single row of detectors and/ormultiple rows of detectors.

The network 120 may include any suitable network that can facilitate theexchange of information and/or data for the data processing system 100.In some embodiments, one or more components (e.g., the scanning device110, the processing device 140, the storage device 150, or the terminaldevice 130) of the data processing system 100 may communicateinformation and/or data with one or more other components of the dataprocessing system 100 via the network 120. For example, the processingdevice 140 may obtain scanning data from the scanning device 110 via thenetwork 120. The network 120 may include a public network (e.g., theInternet), a private network (e.g., a local area network (LAN), a widearea network (WAN), etc.), a wired network (e.g., an Ethernet), awireless network (e.g., an 802.11 network, a wireless Wi-Fi network,etc.), a cellular network (e.g., a long term evolution (LTE) network), aframe relay network, a virtual private network (VPN), a satellitenetwork, a telephone network, routers, hubs, server computers, and/orany combination thereof. For example, the network 120 may include acable network, a wireline network, a fiber-optic network, atelecommunications network, an intranet, a wireless local area network(WLAN), a metropolitan area network (MAN), a public telephone switchednetwork (PSTN), a Bluetooth™ network, a ZigBee™ network, a near fieldcommunication (NFC) network, or the like, or any combination thereof. Insome embodiments, the network 120 may include one or more network accesspoints. For example, the network 120 may include wired and/or wirelessnetwork access points such as base stations and/or internet exchangepoints through which one or more components of the data processingsystem 100 may be connected to the network 120 to exchange data and/orinformation.

The terminal device 130 may be connected to and/or communicate with thescanning device 110, the processing device 140, and/or the storagedevice 150. For example, the terminal device 130 may enable userinteractions with the data processing system 100. In some embodiments,the terminal device 130 may include a mobile device 131, a tabletcomputer 132, a laptop computer 133, or the like, or any combinationthereof. In some embodiments, the mobile device 131 may include a smarthome device, a wearable device, a mobile device, a virtual realitydevice, an augmented reality device, or the like, or any combinationthereof. In some embodiments, the smart home device may include a smartlighting device, a smart electrical appliance control device, a smartmonitoring device, a smart TV, a smart camera, a walkie-talkie, or thelike, or any combination thereof. In some embodiments, the wearabledevice may include bracelets, footwear, glasses, helmets, watches,clothes, backpacks, smart accessories, or the like, or any combinationthereof. In some embodiments, the mobile device may include a mobilephone, a personal digital assistant (PDA), a game device, a navigationdevice, a POS device, a notebook computer, a tablet computer, a desktopcomputer, or the like, or any combination thereof. In some embodiments,the virtual reality device and/or the augmented reality device mayinclude a virtual reality helmet, virtual reality glasses, a virtualreality patch, an augmented reality helmet, augmented reality glasses,an augmented reality patch, or the like, or any combination thereof. Forexample, the virtual reality device and/or augmented reality device mayinclude Google Glass™, Oculus Rift™, HoloLens™, Gear VR™, or the like.In some embodiments, the terminal device 130 may be part of theprocessing device 140.

The processing device 140 may process data and/or information obtainedfrom the scanning device 110, the terminal device 130, and/or thestorage device 150. For example, the processing device 140 may determinescanning data sets needed for image reconstruction. In some embodiments,the processing device 140 may be used to process the scanning data sets,for example, data pre-processing, image reconstruction,post-reconstruction processing, etc. In some embodiments, the processingdevice 140 may be a single server or a group of servers. The servergroup can be centralized or distributed. In some embodiments, theprocessing device 140 may be local to or remote from the data processingsystem 100. For example, the processing device 140 may accessinformation and/or data from the scanning device 110, the storage device150, and/or the terminal device 130 via the network 120. As anotherexample, the processing device 140 may be directly connected to thescanning device 110, the terminal device 130, and/or the storage device150 to access information and/or data. In some embodiments, theprocessing device 140 may be implemented on a cloud platform. Forexample, the cloud platform may include a private cloud, a public cloud,a hybrid cloud, a community cloud, a distributed cloud, and inter-cloud,a multi-cloud, or the like, or a combination thereof. In someembodiments, the processing device 140 may be implemented by a computingdevice 200 having one or more components as described in connection withFIG. 2 .

The storage device 150 may store data (e.g., scanning data of a scanningobject), instructions, and/or any other information. In someembodiments, the storage device 150 may store data obtained from thescanning device 110, the terminal device 130, and/or the processingdevice 140. For example, the storage device 150 may store the scanningdata of the scanning object obtained from the scanning device 110. Insome embodiments, the storage device 150 may store data and/orinstructions that the processing device 140 may execute or use toperform exemplary methods described in the present disclosure. In someembodiments, the storage device 150 may include a mass storage device, aremovable storage device, a volatile read-and-write memory, a read-onlymemory (ROM), or the like, or any combination thereof. Exemplary massstorage devices may include a magnetic disk, an optical disk, asolid-state drive, etc. Exemplary removable storage devices may includea flash drive, a floppy disk, an optical disk, a memory card, a zipdisk, a magnetic tape, etc. Exemplary volatile read-and-write memory mayinclude a random access memory (RAM). Exemplary RAM may include adynamic RAM (DRAM), a double date rate synchronous dynamic RAM (DDRSDRAM), a static RAM (SRAM), a thyristor RAM (T-RAM), and azero-capacitor RAM (Z-RAM), etc. Exemplary ROM may include a mask ROM(MROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM),an electrically erasable programmable ROM (EEPROM), a compact disk ROM(CD-ROM), and a digital versatile disk ROM, etc. In some embodiments,the storage device 150 may be implemented on a cloud platform asdescribed elsewhere in the disclosure.

In some embodiments, the storage device 150 may be connected to thenetwork 120 to communicate with one or more other components (e.g., theprocessing device 140, the terminal device 130) of the data processingsystem 100. One or more components of the data processing system 100 mayaccess the data or instructions stored in the storage device 150 via thenetwork 120. In some embodiments, the storage device 150 may be part ofthe processing device 140, or directly or indirectly connected to theprocessing device 140.

This description is intended to be illustrative, and not to limit thescope of the present disclosure. Many alternatives, modifications, andvariations will be apparent to those skilled in the art. The features,structures, methods, and other characteristics of the exemplaryembodiments described herein may be combined in various ways to obtainadditional and/or alternative exemplary embodiments. However, thosevariations and modifications do not depart the scope of the presentdisclosure

FIG. 2 is a schematic diagram illustrating exemplary hardware componentsand/or software components of an exemplary computing device according tosome embodiments of the present disclosure. In some embodiments, theprocessing device 140 may be implemented on the computing device 200. Asillustrated in FIG. 2 , the computing device 200 may include a processor210, a storage 220, an input/output (I/O) 230, and a communication port240.

The processor 210 may execute computer instructions (e.g., program code)and perform functions of the processing device 140 in accordance withtechniques described herein. The computer instructions may include, forexample, routines, programs, objects, components, data structures,procedures, modules, and functions, which perform particular functionsdescribed herein. For example, the processor 210 may process scanningdata obtained from the scanning device 110, the terminal device 130, thestorage device 150, and/or any other component of the data processingsystem 100. In some embodiments, the processor 210 may include one ormore hardware processors, such as a microcontroller, a microprocessor, areduced instruction set computer (RISC), an application-specificintegrated circuit (ASICs), an application-specific instruction-setprocessor (ASIP), a central processing unit (CPU), a graphics processingunit (GPU), a physics processing unit (PPU), a microcontroller unit, adigital signal processor (DSP), a field programmable gate array (FPGA),an advanced RISC machine (ARM), a programmable logic device (PLD), anycircuit or processor capable of executing one or more functions, or thelike, or any combinations thereof.

Merely for illustration, only one processor is described in thecomputing device 200. However, it should be noted that the computingdevice 200 in the present disclosure may also include multipleprocessors, and thus operations and/or method operations that areperformed by one processor as described in the present disclosure mayalso be jointly or separately performed by the multiple processors. Forexample, if in the present disclosure the processor of the computingdevice 200 executes both operation A and operation B, it should beunderstood that operation A and operation B may also be performed by twoor more different processors jointly or separately in the computingdevice 200 (e.g., a first processor executes operation A and a secondprocessor executes operation B, or the first and second processorsjointly execute operations A and B)

The storage 220 may store data/information obtained from the scanningdevice 110, the terminal device 130, the storage device 150, and/or anyother component of the data processing system 100. In some embodiments,the storage 220 may include a mass storage device, a removable storagedevice, a volatile read-and-write memory, a read-only memory (ROM), orthe like, or any combination thereof. In some embodiments, the storage220 may store one or more programs and/or instructions to performexemplary methods described in the present disclosure. For example, thestorage 220 may store a program for the processing device 140 forreconstructing multiple-phase images of a scanning object based on onceretrieved scanning data sets.

The I/O 230 may input and/or output signals, data, information, etc. Insome embodiments, the I/O 230 may enable a user interaction with theprocessing device 140. In some embodiments, the I/O 230 may include aninput device and an output device. Exemplary input devices may include akeyboard, a mouse, a touch screen, a microphone, or the like, or acombination thereof. Exemplary output devices may include a displaydevice, a loudspeaker, a printer, a projector, or the like, or acombination thereof. Exemplary display devices may include a liquidcrystal display (LCD), a light-emitting diode (LED)-based display, aflat panel display, a curved screen, a television device, a cathode raytube (CRT), a touch screen, or the like, or a combination thereof.

The communication port 240 may be connected to a network (e.g., thenetwork 120) to facilitate data communications. The communication port240 may establish connections between the processing device 140 and thescanning device 110, the terminal device 130, and/or the storage device150. The connection may be a wired connection, a wireless connection,any other communication connection that can enable data transmissionand/or reception, and/or any combination of these connections. The wiredconnection may include, for example, an electrical cable, an opticalcable, a telephone wire, or the like, or any combination thereof. Thewireless connection may include, for example, a Bluetooth™ link, aWi-FiTM link, a WiMax™ link, a WLAN link, a ZigBee™ link, a mobilenetwork link (e.g., 3G, 4G, 5G), or the like, or a combination thereof.In some embodiments, the communication port 240 may be and/or include astandardized communication port, such as RS232, RS485, etc. In someembodiments, the communication port 240 may be a specially designedcommunication port. For example, the communication port 240 may bedesigned in accordance with the digital imaging and communications inmedicine (DICOM) protocol.

FIG. 3 is a schematic diagram illustrating exemplary hardware componentsand/or software components of an exemplary mobile device according tosome embodiments of the present disclosure. In some embodiments, one ormore components (e.g., the terminal device 130 and/or the processingdevice 140) of the data processing system 100 may be implemented on themobile device 300.

As illustrated in FIG. 3 , the mobile device 300 may include a display310, a communication platform 320, a graphic processing unit (GPU) 330,a central processing unit (CPU) 340, an I/O 350, a memory 360, and astorage 390. In some embodiments, any other suitable component,including but not limited to a system bus or a controller (not shown),may also be included in the mobile device 300. In some embodiments, amobile operating system 370 (e.g., iOS™, Android™, Windows Phone™) andone or more applications 380 may be loaded into the memory 360 from thestorage 390 in order to be executed by the CPU 340. The applications 380may include a browser or any other suitable mobile apps for receivingand rendering information relating to image processing or otherinformation from the processing device 140. User interactions with theinformation stream may be achieved via the I/O 350 and provided to theprocessing device 140 and/or other components of the data processingsystem 100 via the network 120.

To implement various modules, units, and their functionalities describedin the present disclosure, computer hardware platforms may be used asthe hardware platform(s) for one or more of the elements describedherein. A computer with user interface elements may be used to implementa personal computer (PC) or any other type of work station or terminaldevice. A computer may also act as a server if appropriately programmed.

FIG. 4 is a flowchart illustrating an exemplary process for processingscanning data of a scanning object during a scanning process accordingto some embodiments of the present disclosure. In some embodiments, theprocess 400 may be implemented in the data processing system 100illustrated in FIG. 1 . For example, the process 400 may be stored in astorage medium (e.g., the storage device 150, or the storage 220 of theprocessing device 140) as a form of instructions, and can be invokedand/or executed by the processing device 140 (e.g., the processor 210 ofthe processing device 140, or one or more modules in the processingdevice 140 illustrated in FIG. 8 ). The operations of the illustratedprocess 400 presented below are intended to be illustrative. In someembodiments, the process 400 may be accomplished with one or moreadditional operations not described, and/or without one or more of theoperations discussed. Additionally, the order in which the operations ofthe process 400 as illustrated in FIG. 4 and described below is notintended to be limiting.

In 410, the processing device 140 (e.g., the acquisition module 810) maydetermine at least two target phases of a motion of a scanning object.The at least two target phases may be within a scanning process thatinvolves multiple data acquisition time points each of which correspondsto a scanning data set.

As used herein, a target phase corresponds to a certain time period in amotion cycle during which the scanning object is at a specific state(e.g., a gentle state) of a motion of interest. The motion of interestmay be a physiological motion including, e.g., a cardiac motion, arespiratory motion, etc. The scanning object may be biological ornon-biological. For example, the scanning object may include a patient,an animal (e.g., an experimental mouse), a man-made object, etc. In someembodiments, the scanning object may include a specific portion, organ,and/or tissue of the patient. For example, the scanning object mayinclude the heart, lungs, ribs, the abdominal cavity, the head, thebrain, the stomach, the neck, soft tissues, or the like, or anycombination thereof, of the patient. For illustration purposes, theheart is taken as an example of the scanning object in the presentdisclosure. It should be noted that the term “scanning object,” “scannedobject,” “patient,” and “heart” are used interchangeably in the presentdisclosure, in which the magnitude of the cardiac motion is relativelysmall as compared to the rest of a motion cycle of the cardiac motion.

In some embodiments, the target phase may be represented by acharacteristic value between 0 and 1, such as 0.2 or 0.8. Thecharacteristic value may indicate where the target phase is in themotion cycle. In some embodiments, the characteristic value may be aratio of a characteristic motion magnitude corresponding to the targetphase to the maximum magnitude of the motion cycle of the motion ofinterest of the scanning object. As the target phase corresponds to afirst time period, the motion magnitude within the target phase maychange over time. The characteristic motion magnitude of the targetphase may be an average of the motion magnitude in the target phase, orthe motion magnitude at a reference time point of the target phase. Forinstance, the characteristic motion magnitude of the target phase may bethe motion magnitude at the starting time point, the ending time point,the target data acquisition time point, etc., of the target phase.

In some embodiments, the characteristic value may be a ratio of theduration from a reference time point of the motion cycle (e.g., astarting time point of the motion cycle) to a characteristic time pointin the target phase to the duration of the motion cycle of the motion ofinterest of the scanning object. In some embodiments, the characteristictime point in the target phase may be a midpoint, or any other timepoint (e.g., the starting time point, the ending time point) of thetarget phase (or the first time period corresponding to the targetphase).

It should be understood that a motion cycle as used herein refers to amotion interval or duration in which the scanning object starts to movefrom an initial state and returns to the initial state afterexperiencing multiple different states. In some embodiments, in specificmotion cycles of the scanning object, the movement of the scanningobject may be repeated. That is, the motion intervals/durations of thespecific motion cycles may be the same. Accordingly, the characteristicvalue representing a target phase may indicate where the target phase isin each of one or more motion cycles. A target phase may correspond to acertain motion state of the motion of interest of the scanning object.In some embodiments, in specific motion cycles of the scanning object,the movement of the scanning object may be irregular, instead of regularor cyclic. The motion intervals/durations of at least two consecutivemotion cycles of the specific motion cycles may be different.

In some embodiments, information of the at least two target phases maybe pre-stored in a storage device (e.g., the storage device 150 or thestorage 220). The processing device 140 may identify the at least twotarget phases based on physiological attributes (e.g., age, gender,etc.) of the scanning object. In some embodiments, the at least twotarget phases may be identified by a user through one or more terminals(e.g., the terminal device 130). In some embodiments, the at least twotarget phases may be determined according to practical needs. Forexample, patients of different ages and/or genders may have differenttarget phases.

In 420, the processing device 140 (e.g., the determination module 820)may identify at least two first time periods during the scanningprocess. Each of the at least two first time periods may correspond toone of the at least two target phases.

In some embodiments, the processing device 140 may identify at least twotarget data acquisition time points each of which corresponds to one ofthe at least two target phases during the scanning process.

As used herein, the scanning process refers to a scan of the scanningobject. In some embodiments, the scanning process may be performedwithin one or more motion cycles of the motion of interest. In someembodiments, the processing device 140 may designate one of the one ormore motion cycles as a target motion cycle. For example, the processingdevice 140 may identify the longest motion cycle from the one or moremotion cycles, and designate the longest motion cycle as the targetmotion cycle. Scanning data corresponding to a specific time periodwithin the target motion cycle may be retrieved for imagereconstruction. In some embodiments, the processing device 140 maydesignate at least two of the motion cycles as target motion cycles. Forexample, assuming that the duration of a motion cycle is T, the durationof the scanning process may be (α+N)×T, in which a is a real numberbetween 0 and 1, and N is zero or a positive integer. In someembodiments, scanning data corresponding to a specific time periodwithin each of the at least two motion cycles may be retrieved for imagereconstruction. For example, scanning data corresponding to a timeperiod represented by 0.2T-0.8T of each of the at least two motioncycles may be used for reconstructing one or more phase images each ofwhich corresponds to a target phase.

FIG. 9A is a diagram illustrating an exemplary process for acquiringmultiple scanning data sets during a scanning process according to someembodiments of the present disclosure. As illustrated in FIG. 9A, RTag1,RTag2, and RTag3 represent signals of three consecutive heartbeatsdetected by an electrocardiogram (ECG) monitor. Thus, a duration betweeneach two consecutive heartbeats may be a duration of a motion cycle ofthe cardiac motion. The radiation source 115 may emit radiation beams attime points within the time period AB of each motion cycle. Scanningdata sets each of which corresponds to a data acquisition time pointduring the time period AB of each motion cycle may be acquired togenerate phase images of different phases of the cardiac motion of theheart.

During the scanning process, the radiation source 115 may rotate aroundthe scanning object for scanning. The radiation source 115 may emit aradiation beam at a specific time point based on a scanning protocol,and the detector(s) 112 may detect at least a portion of the radiationbeam to obtain scanning data (or scanning data sets). Each time pointmay be referred to as a data acquisition time point. Since the radiationsource 115 is rotating, each data acquisition time point may correspondto a data acquisition angle. As used herein, a data acquisition anglerefers to the rotation angle of the radiation source at thecorresponding data acquisition time point with respect to a referencedirection (e.g., the vertical direction perpendicular to the floor wherethe scanning device 110 is supported). At the same time, each dataacquisition time point may correspond to a set of scanning data (or ascanning data set). That is, the scanning process may involve multipledata acquisition time points each of which corresponds to a scanningdata set acquired when the radiation source is at a specific dataacquisition angle. It should be noted that the term “scanning data” or“scanning data set(s)” may be used interchangeably in the presentdisclosure.

In some embodiments, a target phase may correspond to a time periodcentered on a target data acquisition time point. A data acquisitiontime point that is the same as or closest, among the plurality ofmultiple data acquisition time points of the scanning process, to anestimated target data acquisition time point (or referred to as a presettime point) may be designated as the target data acquisition time pointcorresponding to the target phase. Because the scanning process involvesa large number of data acquisition time points within the duration ofeach motion cycle, a time duration between two adjacent data acquisitiontime points is short. For example, a motion cycle of the cardiac motionis roughly 0.8 s, and the scanning process performed in one motion cycleof the cardiac motion may have 4200 data acquisition time points. A dataacquisition time point during the scanning process that is the same asor the closest, among the plurality of multiple data acquisition timepoints of the scanning process, to the estimated target data acquisitiontime point may be designated as the target data acquisition time pointcorresponding to a target phase. In some embodiments, the processingdevice 140 may determine the target data acquisition time pointcorresponding to a target phase based on the starting time point and theending time point of a motion cycle of a motion of interest of thescanning object in combination with the value representing the targetphase. More descriptions regarding the determination of the target dataacquisition time point corresponding to a target phase may be foundelsewhere in the present disclosure (e.g., FIG. 6 and the descriptionsthereof).

In some embodiments, the processing device 140 (e.g., the determinationmodule 820) may determine, based on the target data acquisition timepoint corresponding to each of the at least two target phases, a firsttime period corresponding to each of the at least two target phases.

It can be understood that for a target phase, using an imagereconstruction algorithm to generate a reconstructed image of thescanning object needs a plurality of scanning data. The first timeperiod may include data acquisition time points corresponding toscanning data sets needed to reconstruct an image (or phase image) ofthe scanning object of the target phase. An image of a target phase maypossess a desired image quality. In some embodiments, the image qualitymay be assessed in terms of an image resolution with respect to an imageresolution threshold, an image contrast with respect to an imagecontrast threshold, or the like, or a combination thereof.

In some embodiments, the first time period may be a time periodincluding the target data acquisition time point of the target phase.For example, the processing device 140 may select a time period centeredon the target data acquisition time point corresponding to the targetphase as the first time period. As another example, the processingdevice 140 may arbitrarily select a time period including the targetdata acquisition time point of the target phase as the first timeperiod. Correspondingly, the target data acquisition time pointcorresponding to the target phase may be the midpoint of the first timeperiod, or any time point in the first time period. In some embodiments,the at least two first time periods may fall within a range within themotion cycle of the scanning object. The range may include a portion orall of the motion cycle. More descriptions regarding determining thefirst time period may be found elsewhere in the present disclosure(e.g., FIG. 5 and the descriptions thereof).

In 430, the processing device 140 (e.g., the determination module 820)may determine a second time period that encloses the at least two firsttime periods.

In some embodiments, the first time periods corresponding to the atleast two target phases may overlap. That is to say, same secondscanning data sets corresponding to the overlapping portion of the atleast two target phases may need to be involved in the reconstruction ofphase images of the scanning object of the at least two target phases.For example, the scanning data set acquired at a certain dataacquisition time point can be used to reconstruct two or more phaseimages each of which corresponds to a target phase. As describedelsewhere in the present disclosure, in a single-phase imagereconstruction, scanning data acquired in a time period (e.g., the firsttime period) related to one of the at least two target phases isretrieved and subject to image reconstruction separately for each of theat least two target phases. See, e.g., FIG. 10 and the descriptionthereof. Accordingly, the scanning data corresponding to the overlappingportions of two of the at least two target phases may need to beretrieved and processed (e.g., pre-processed) repeatedly, resulting induplicated efforts.

According to some embodiments of the present disclosure, the processingdevice 140 may determine a time period (the second time period) thatencloses the at least two first time periods; scanning datacorresponding to the at least two first periods may be retrieved and/or(at least partially) processed once to reduce or avoid duplicate effortsin scanning data retrieval and/or processing of same scan data. As usedherein, the second time period refers to a time period corresponding tothe union or a total of the at least two first time periods or thecorresponding target phases. The second time period may include each ofthe at least two first time periods. As a result, the scanning data setscorresponding to the second time period can be retrieved once forfurther processing including, e.g., reconstructing phase imagescorresponding to the target phases or the corresponding first timeperiods.

In some embodiments, the processing device 140 may determine the secondtime period based on the starting time point and the ending time pointof each of the at least two first time periods. For example, theprocessing device 140 may designate one of the starting time points ofthe at least two first time periods as a starting time point of thesecond time period based on a preset rule. The processing device 140 maydesignate one of the ending time points of the at least two first timeperiods as an ending time point of the second time period. Moredescriptions about the determining the second time period may be foundelsewhere in the present disclosure (e.g., FIG. 5 and the descriptionsthereof).

In 450, the processing device 140 (e.g., the retrieval module 830) mayretrieve once, from the multiple scanning data sets, second scanningdata sets for reconstructing phase images of each of which correspondsto one of the at least two target phases. The second scanning data setsmay be acquired at second data acquisition time points of the multipledata acquisition time points within the second time period.

In some embodiments, the multiple scanning data sets generates byscanning the scanning object may first be stored in a storage device(e.g., the storage device 150, the storage 220, or an external storagedevice). In some embodiments, the multiple scanning data sets may bedirectly transmitted to the processing device 140 and/or the processor210 for processing. After the second time period is determined, theprocessing device 140 may retrieval once the second scanning data setsacquired at second data acquisition time points within the second timeperiod from the storage device, or from the received multiple scanningdata sets. In this way, the repeated retrieving of the same scanningdata may be avoided, and the amount of calculation for subsequent dataprocessing may be reduced, thereby saving data processing time.

In some embodiments, after retrieving the second scanning data setsacquired at each data acquisition time point in the second time period,the processing device 140 may generate a phase image related to each ofthe at least two target phases based on the acquired second scanningdata sets. For example, the processing device 140 may pre-process thesecond scanning data sets, and perform image reconstruction for eachtarget phase based on the pre-processed second scanning data sets. Insome embodiments, algorithms used in the pre-processing may include anair calibration algorithm, an inter-layer normalization algorithm, acrosstalk correction algorithm, a nonlinear correction algorithm, a CTvalue calibration (HU) algorithm, a bad channel correction algorithm, abeam hardening correction algorithm, or the like, or any combinationthereof. More descriptions for generating the reconstructed image of thescanning object may be found elsewhere in the present disclosure (e.g.,FIG. 7 and the descriptions thereof).

In the present disclosure, the acquired second scanning data sets onlyneed to be pre-processed once, and then can be used for reconstructingthe phase images of the at least two target phases. See, e.g., FIG. 7and the description thereof. Compared with a single-phase reconstructionthat involves repeated retrieving and repeated processing of scanningdata, according to some embodiments of the present disclosure, thescanning data to be used in subsequent reconstructing phase images ofmultiple phases may be retrieved and pre-processed once, therebyavoiding or reducing duplicate efforts and time consumption inretrieving and pre-processing same scanning data sets involved in thereconstruction of multiple phase images corresponding to target phasesthat partially overlap.

It should be noted that the above descriptions are merely provided forthe purposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

In some embodiments, one or more operations may be omitted and/or one ormore additional operations may be added. For example, the process 400may further include an operation to reconstruct phase images of thescanning object based on the retrieved the second scanning data sets.Additionally or alternatively, the process 400 may further include anoperation for transmitting the generated phase images to a terminaldevice (e.g., the terminal device 130) of a user (e.g., a doctor). Theuser may view the generated images for further treatment. See, e.g.,FIG. 7 and the description thereof.

FIG. 5 is a schematic flowchart illustrating an exemplary process fordetermining a second time period according to some embodiments of thepresent disclosure. In some embodiments, the process 500 may beimplemented in the data processing system 100 illustrated in FIG. 1 .For example, the process 500 may be stored in a storage medium (e.g.,the storage device 150, or the storage 220 of the processing device 140)as a form of instructions, and can be invoked and/or executed by theprocessing device 140 (e.g., the processor 210 of the processing device140, or one or more modules in the processing device 140 illustrated inFIG. 8 ). The operations of the illustrated process 500 presented beloware intended to be illustrative. In some embodiments, the process 500may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process 500 asillustrated in FIG. 5 and described below is not intended to belimiting. In some embodiments, operations 420 may be performed based onthe process 500.

In 510, the processing device 140 (e.g., the determination module 820)may determine a data acquisition angle at a target data acquisition timepoint corresponding to a target phase.

In some embodiments, during a scanning process, the radiation source 115may rotate around the scanning object for scanning. The radiation source115 may emit a radiation beam at a specific time point (e.g., the targetdata acquisition time point) based on a scanning protocol, and thedetector(s) 112 may detect at least a portion of the radiation beam toobtain scanning data. At least a portion of the detected radiation beammay have passed through the scanning object. Since the radiation source115 is rotating, each data acquisition time point may correspond to adata acquisition angle (e.g., the rotation angle of the radiation source115 from a starting data acquisition time point to the data acquisitiontime point). In some embodiments, the scanning data set corresponding toa data acquisition time point may correspond to a set of acquisitioninformation. The acquisition information corresponding to a scanningdata set or its data acquisition time point may include currentinformation of the radiation source 115 (e.g., a tube current of theradiation source 115), a position of the table 114, a tube angle of theradiation source 115 (e.g., the data acquisition angle), a time stamp(e.g., the time stamp of the data acquisition time point), etc., or acombination thereof, when the scanning data set is acquired at the dataacquisition time point. The processing device 140 may determine a targetdata acquisition angle corresponding to a target data acquisition timepoint corresponding to a target phase by querying the acquisitioninformation. More descriptions about the determining a target dataacquisition time point corresponding to a target phase may be foundelsewhere in the present disclosure (e.g., FIG. 6 , and the descriptionsthereof).

In 520, the processing device 140 (e.g., the determination module 820)may determine a first angle range centering at the target dataacquisition angle of the target phase.

It should be understood that image reconstruction using an imagereconstruction algorithm needs more than one scanning data set acquiredat a single data acquisition angle or data acquisition time point.Therefore, in order to perform image reconstruction, multiple scanningdata sets may be needed. Therefore, the processing device 140 mayobtain, for image reconstruction (i.e., reconstructing a phase imagecorresponding to the target phase of the scanning object), multiplescanning data sets acquired at data acquisition time pointscorresponding to the target phase. The scanning data sets may includescanning data acquired at the data acquisition angles within the firstangle range. In some embodiments, the first angle range may bedetermined based on a preset value (e.g., 90°, 180°, 240°, 360°, etc.).In some embodiments, the preset value may be adjusted according topractical needs previously acquired by the processing device 140 orbased on a user instruction.

In 530, the processing device 140 (e.g., the determination module 820)may designate, as the first time period, a plurality of data acquisitiontime points each of which corresponds to a data acquisition angle withinthe first angle range. For example, the processing device 140 may takethe target data acquisition angle corresponding to the target dataacquisition time point as the center of the first angle range, take 90°clockwise and 90° anti-clockwise, and determine a time period composedof the data acquisition time points corresponding to all the dataacquisition angles within the first angle range, and designate the timeperiod as the first time period.

FIG. 9B is a diagram illustrating an exemplary process for determining afirst time period according to some embodiments of the presentdisclosure. As illustrated in FIG. 9B, the radiation source 115 emitsradiation beams at time points within the time period AB of each motioncycle. Then, scanning data sets each of which corresponds to a dataacquisition time point during the time period AB of each motion cycleare acquired. For a target phase P, a target data acquisition time point(i.e., phase point 1 or phase point 2) corresponding to the target phaseP of each motion cycle may be determined according to Equation (1)described in connection with 620. Then a first time period ab (e.g.,first time period 1, first time period 2) corresponding to the targetphase X is determined by centering on a target data acquisition anglecorresponding to the target phase P. The scanning data sets acquiredduring the first time period ab may be used for reconstructing a phaseimage of the target phase P.

In some embodiments, the processing device 140 (e.g., the determinationmodule 820) may determine a second time period that encloses the atleast two first time periods.

In some embodiments, the processing device 140 may identify a startingtime point and an ending time point for each of the two first timeperiods. For each of the at least two first time periods, the startingtime point may be a data acquisition time point corresponding to thesmallest data acquisition angle within the first angle range of thefirst time period; the ending time point may be a data acquisition timepoint corresponding to the largest data acquisition angle within thefirst angle range of the first time period. For example, if the targetdata acquisition angle at the target data acquisition time pointcorresponding to the target phase is 270°, and the first angle range is360°, the starting time point of one of the at least two first timeperiods may be the data acquisition time point corresponding to the dataacquisition angle of 90° ; the ending time point of the same first timeperiod may be a data acquisition time point corresponding to the dataacquisition angle of 450°. In some embodiments, the processing device140 may determine the starting time point and the ending time point of afirst time period by querying the acquisition information. Theprocessing device 140 may designate an earlier starting time point ofthe at least two starting time points of the at least two first timeperiods as a starting time point of the second time period. Theprocessing device 140 may designate a later ending time point of the atleast two ending time points of the at least two first time periods asan ending time point of the second time period.

FIG. 9C is a diagram illustrating an exemplary process for determining asecond time period during a motion cycle (e.g., [RTag1, RTag2]) of amotion of a scanning object according to some embodiments of the presentdisclosure. As illustrated in FIG. 9C, three target phases each of whichcorresponds a target data acquisition time point (or referred to as“phase point” for brevity) include target phase 1, target phase 2, andtarget phase 3, and the first time period 1 corresponding to targetphase 1 is [S1, E1], where S1 and E1 denote the starting time point andthe ending time point of the first time period 1, respectively; thefirst time period 2 corresponding to target phase 2 is [S2, E2], whereS2 and E2 denote the starting time point and the ending time point ofthe first time period 2, respectively; the first time period 3corresponding to target phase 3 is [S3, E3], where S3 and E3 denote thestarting time point and the ending time point of the first time period3, respectively. The processing device 140 may determine a minimumstarting time point S (e.g., S=min (S1, S2, S3)) (i.e., the earlieststarting time point) among the three starting time points (S1, S2, S3).The processing device 140 may determine a maximum ending time point E(e.g., E=max (E1, E2, E3)) (i.e., the latest ending time point) amongthe three ending time points (E1, E2, E3). The processing device 140 maydesignate the minimum starting time point S as the starting time pointof the second time period and the maximum ending time point E as theending time point of the second time period. The second time period maybe determined as [S, E] (i.e., [S1, E3]). Accordingly, the second timeperiod may enclose the three first time periods. In some embodiments,the processing device 140 may retrieve once scanning data acquiredduring the second time period. That is, the processing device 140 mayretrieve scanning data acquired during the second time periods [S1, E3]of one or more target motion cycles in one data retrieval operation.

It should be noted that when the two first time periods corresponding tothe two target phases of the scanning object overlap, and scanning dataacquired in each first time period is retrieved and subject to imagereconstruction separately for each of the two target phases, thescanning data corresponding to an overlapping portion of the two targetphases may need to be retrieved and processed (e.g., pre-processed)repeatedly, resulting in duplicated efforts. As described elsewhere inthe present disclosure, by retrieving and/or pre-processing image datacorresponding to multiple target phases together, repeated dataretrieval and/or pre-processing can be reduced or avoided.

It should be noted that the above descriptions are merely provided forthe purposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. In someembodiments, one or more operations may be omitted and/or one or moreadditional operations may be added. For example, the process 500 mayfurther include an operation for storing information (e.g.,corresponding data acquisition time points in the first time periodand/or the second time period). A user (e.g., a doctor) may performdiagnosis and/or treatment based on the generated phase images.

FIG. 6 is a schematic flowchart illustrating an exemplary process fordetermining a target data acquisition time point corresponding to atarget phase associated with a scanning process according to someembodiments of the present disclosure. In some embodiments, the process600 may be implemented in the data processing system 100 illustrated inFIG. 1 . For example, the process 600 may be stored in a storage medium(e.g., the storage device 150, or the storage 220 of the processingdevice 140) as a form of instructions, and can be invoked and/orexecuted by the processing device 140 (e.g., the processor 210 of theprocessing device 140, or one or more modules in the processing device140 illustrated in FIG. 8 ). The operations of the illustrated process600 presented below are intended to be illustrative. In someembodiments, the process 600 may be accomplished with one or moreadditional operations not described, and/or without one or more of theoperations discussed. Additionally, the order in which the operations ofthe process 600 as illustrated in FIG. 6 and described below is notintended to be limiting. In some embodiments, operation 510 may beperformed based on the process 600.

In 610, the processing device 140 (e.g., the determination module 820)may identify a starting time point and an ending time point of a targetmotion cycle of a motion of interest of a scanning object.

For example, when the scanning object is the heart of a patient, themotion of interest may be cardiac motion, and the target motion cyclemay be a time period between two consecutive heartbeats, which may alsobe referred to as a cardiac cycle. In some embodiments, the targetmotion cycle may be determined by a monitoring device, such as anelectrocardiogram (ECG) monitor. By the ECG monitor, a time periodbetween two consecutive R waves may be identified as a cardiac cycle. Atthe same time, the monitoring device used to monitor the target motioncycle may record time information related to the target motion cycle,including the starting time point and the ending time point of thetarget motion cycle. For example, the ECG monitor may record time stampsof the two consecutive R waves in the cardiac cycle. A time stamp of thepreceding R wave of the two consecutive R waves may correspond to thebeginning of the cardiac cycle, and a time stamp of the next R wave ofthe two consecutive R waves may correspond to the end of the cardiaccycle. For two consecutive cardiac cycles, the end of the precedingcardiac cycle may coincide with the beginning of the following cardiaccycle. Based on the time information related to the target motion cycle,the processing device 140 may directly determine the starting time pointand the ending time point of the cardiac cycle. For example, themonitoring device used to monitor the target motion cycle may send thetime information related to the target motion cycle to the processingdevice 140 through wired or wireless transmission. In some embodiments,the starting time point and the ending time point of the target motioncycle may be represented by the time stamps.

In 620, the processing device 140 (e.g., the determination module 820)may identify, based on a target phase, the starting time point of thetarget motion cycle, and the ending time point of the target motioncycle, a preset time point (or referred to as estimated target dataacquisition time point). The preset time point may correspond to thetarget phase within the target motion cycle.

In some embodiments, the target phase may be represented by acharacteristic value from 0 to 1. More descriptions regarding thecharacteristic value may be found elsewhere in the present application.See, e.g., 410 in FIG. 4 and the description thereof. The characteristicvalue representing the target phase may also indicate a state of themotion of interest (e.g., the cardiac motion) of the scanning object ata data acquisition time point corresponding to the target phase in thetarget motion cycle. For example, if the target motion cycle of thescanning object is T, and the characteristic value used to represent thetarget phase is 0.4, the scanning object may be in a state correspondingto a time point of 0.4T from the starting time point of the targetmotion cycle; the cardiac motion may be in a relatively gentle state at0.4T in which the magnitude of the cardiac motion is relatively small ascompared to the rest of the target motion cycle of the cardiac motion.In some embodiments, the preset time point may be a specific time pointrepresenting the target phase, for example, a specific time pointcorresponding to 0.4T from a reference time point of the target motioncycle (e.g., the starting time point of the target motion cycle). Merelyby way of example, if T=0.8 s, the scanning object may be in the targetphase at the time point (determined based on, e.g., a time stamp)corresponding to 0.32 s from a reference time point of the target motioncycle (e.g., the starting time point of the target motion cycle).

In some embodiments, the processing device 140 may determine the presettime point based on Equation (1):

Tpp=T1*(1−p)+T2*p,   (1)

where T1 denotes the starting time point of the target motion cycle, T2denotes the ending time point of the target motion cycle, p denotes acharacteristic value representing the target phase (0<p<1), and Tppdenotes the preset time point. The processing device 140 may input thestarting time point of the target motion cycle, the ending time point ofthe target motion cycle, and the characteristic value representing thetarget phase into Equation (1) to determine the preset time pointcorresponding to the target phase.

In 630, the processing device 140 (e.g., the determination module 820)may determine whether there is a data acquisition time point amongmultiple data acquisition time points that coincides with the presettime point corresponding to the target phase. The multiple dataacquisition time points may be involved in the scanning process of thescanning object, each of which corresponds to a scanning data set.

In some embodiments, the processing device 140 may compare the presettime point with the multiple data acquisition time points, or a portionthereof. In response to determining that there is a data acquisitiontime point, among the multiple data acquisition time points, thatcoincides with the preset time point, the processing device 140 mayproceed to perform operation 650. In response to determining that thereis no data acquisition time point, among the multiple data acquisitiontime points, that coincides with the preset time point, the processingdevice 140 may proceed to perform operation 640.

In 640, the processing device 140 (e.g., the determination module 820)may determine a data acquisition time point whose difference withrespect to the preset time point is minimal among the multiple dataacquisition time points.

When there is no data acquisition time point, among the multiple dataacquisition time points, that coincides with the preset time point, adata acquisition time point that is closest to the preset time point,among the multiple data acquisition time points, may be determined. Forinstance, the processing device 140 may determine the difference betweenthe preset time point and each of the multiple data acquisition timepoints to determine, based on the differences, the data acquisition timepoint closest to the preset time point, among the multiple dataacquisition time points.

In 650, the processing device 140 (e.g., the determination module 820)may designate the determined data acquisition time point as the targetdata acquisition time point corresponding to the target phase. Thedetermined data acquisition time point may coincide with the presenttime point or be closest to the preset time point, among the multipledata acquisition time points.

It should be noted that the above descriptions are merely provided forthe purposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. In someembodiments, one or more operations may be omitted and/or one or moreadditional operations may be added. For example, the process 600 mayfurther include an operation for storing information and/or data (e.g.,the target data acquisition time point corresponding to the targetphase) in the storage device 150.

FIG. 7 is a schematic flowchart illustrating an exemplary process forreconstructing multiple-phase images of a scanning object according tosome embodiments of the present disclosure. In some embodiments, theprocess 700 may be implemented in the data processing system 100illustrated in FIG. 1 . For example, the process 700 may be stored in astorage medium (e.g., the storage device 150, or the storage 220 of theprocessing device 140) as a form of instructions, and can be invokedand/or executed by the processing device 140 (e.g., the processor 210 ofthe processing device 140, or one or more modules in the processingdevice 140 illustrated in FIG. 8 ). The operations of the illustratedprocess 700 presented below are intended to be illustrative. In someembodiments, the process 700 may be accomplished with one or moreadditional operations not described, and/or without one or more of theoperations discussed. Additionally, the order in which the operations ofthe process 700 as illustrated in FIG. 7 and described below is notintended to be limiting.

In 710, the processing device 140 (e.g., the reconstruction module 840)may obtain a second scanning data set of a plurality of second scanningdata sets acquired during a second time period. The second time periodmay include at least two first time periods as described in connectionwith operation 430 in FIG. 4 .

It should be noted that when the image reconstruction process starts,the processing device 140 may initialize parameters of one or morealgorithms (e.g., a preprocessing algorithm, an image reconstructionalgorithm, a post-processing algorithm, etc.) of the imagereconstruction process.

In 720, the processing device 140 (e.g., the reconstruction module 840)may process the second scanning data set and store the second scanningdata set in a group.

In some embodiments, the processing device 140 may pre-process thesecond scanning data set. In some embodiments, the processing device 140may pre-process the second scanning data set using a pre-processingalgorithm to make the pre-processed second scanning data sets suitablefor subsequent image reconstruction operations. In some embodiments, thepre-processing algorithm may include an air calibration algorithm, aninter-layer normalization algorithm, a crosstalk correction algorithm, anonlinear correction algorithm, a CT value calibration (HU) algorithm, abad channel correction algorithm, a beam hardening correction algorithm,or the like, or any combination thereof. In some embodiments, theprocessing device 140 may further perform a data rearrangement and/orfiltering on the second scanning data sets to simplify subsequent imagereconstruction process. In some embodiments, the data rearrangementand/or filtering may include using an AziRebin algorithm, a RadialRebinalgorithm, a QSRebin algorithm, a filtering algorithm, etc.

In some embodiments, after pre-process the second scanning data set, theprocessing device 140 may assign the pre-processed second scanning dataset into a group corresponding to the first time period of the targetphase, and store the group into a first storage device (e.g., thestorage device 150). That is, the processing device 140 may identify towhich of target phases the data acquisition time point corresponding tothe second scanning data set corresponds. The processing device 140 mayidentify to which of the target phases the second data acquisition timepoint corresponds by identifying to which of the first time periods thesecond data acquisition time point belongs. For example, the processingdevice 140 may compare the second data acquisition time point with atime range corresponding to each of the first time periods. Theprocessing device 140 may identify to which of the first time periodsthe second data acquisition time point belongs based on a comparisonresult. When the processing device 140 determines that the second dataacquisition time point belongs to a certain one of the first timeperiods, the processing device 140 may determine that the second dataacquisition time point corresponds to the certain target phasecorresponding to the certain first time period. For example, a certainsecond data acquisition time point 1 is 0.25T′ (from a reference timepoint, e.g., the starting time point of the target motion cycle),another second data acquisition time point 2 is 0.35T′ (from a referencetime point, e.g., the starting time point of the target motion cycle), atime range of the first time period related to a target phase 1 is(0.2T′-0.4T′), and a time range of the first time period related to atarget phase 2 is (0.3T′-0.5T′), where T′ denotes a virtual time point(from a reference time point, e.g., the starting time point of thetarget motion cycle); the processing device 140 may determine that thesecond data acquisition time point 1 belongs to the time range of thefirst time period related to the target phase 1 (0.25T′∈(0.2T′-0.4T′)),and the second data acquisition time point 2 belongs to the time rangeof the first time period related to the target phase 1(0.35T′∈(0.2T′-0.4T′)) and also the time range of the first time periodrelated to the target phase 2 (0.35T′∈(0.3T′-0.5T′)). Therefore, theprocessing device 140 may determine that the second data acquisitiontime point 1 corresponds to the target phase 1, and the second dataacquisition time point 2 corresponds to the target phase 1 and also thetarget phase 2.

In some embodiments, the processing device 140 may sequentially numbereach data acquisition angle corresponding to each second scanning dataset in an ascending order or descending order. Because each dataacquisition angle corresponds to one of the second data acquisition timepoints, each first time period may correspond to a range of the dataacquisition angles. The processing device 140 may determine to whichdata acquisition angle range (or referred to as angle range) the dataacquisition angle corresponding to the second data acquisition timepoint belongs. The processing device 140 may identify to which of thetarget phases the second data acquisition time point corresponds basedon a result of the determination with respect to the angle range. Forexample, the processing device 140 may index the data acquisition anglescorresponding to the plurality of second data acquisition time points inthe second time period by, e.g., numbering them according to anascending order, for example, from 1 to 1200. The processing device 140may determine the index range of the data acquisition angles for a firsttime period based on the data acquisition angles corresponding to astarting time point and an ending time point of the first time period.For example, the index of a certain data acquisition angle correspondingto a certain second data acquisition time point is 800, the index rangeof one of the first time periods related to a target phase 1 is[1-1000], the index range of another one of the first time periodsrelated to another target phase 2 is [601-1500]; the processing device140 may determine that the certain second data acquisition time pointbelongs to the first time period related to the target phase 1(800∈[1-1000]) and also the first time period related to the targetphase 2 (800∈[601-1500]). Therefore, the processing device 140 maydetermine that the certain second data acquisition time pointcorresponds to the target phase 1 and the target phase 2.

In some embodiments, the processing device 140 may determine whether thesecond scanning data set satisfies a compliance condition, for example,an index of the second scanning data set exceeding an index thresholdindicating that there is sufficient scanning data in the group forconstructing a phase image. In response to determining that the secondscanning data set satisfies the compliance condition, the processingdevice 140 may proceed to reconstruct a phase image of the correspondingtarget phase of the scanning object based on the second scanning datasets stored in the corresponding group using an image reconstructionalgorithm.

For example, the plurality of second scanning data sets each of whichcorresponds to an index may be represented by index values 1-1000, whereindexes of the second scanning data sets corresponding to one first timeperiod of target phase 1 are 1-600 and indexes of the second scanningdata sets corresponding to another one first time period of target phase2 are 400-1000. The processing device 140 may determine the compliancecondition is that the index of a second scanning data set is equal tothe maximum index of indexes of a first time period. During an imagereconstruction process in which a plurality of second scanning data setsindexed as 1st-1000th second scanning data sets are processed one by oneaccording to an ascending order, i.e., from the 1st to the 1000th secondscanning data sets, when the processing device 140 processes the i-th(0<i<1000) second scanning data set, the processing device 140 maydetermine whether i is equal to 600 or 1000. When it is determined thati is smaller than 600, the processing device 140 may not reconstruct aphase image based on the second scanning data sets 1 to i (i.e.,scanning data in a group corresponding to the [1-600], and return to 710as shown in connection with 730. When it determines that i is equal toor greater than 600, the processing device 140 may reconstruct a phaseimage based on the second scanning data sets 1 to i in the group.

Moreover, for a second scanning data set that is determined to belong tomore than one target phases, e.g., the second scanning data set 600determined to belong to target phase 1 and target phase 2, theprocessing device 140 may store such a second scanning data set intogroups corresponding to target phases 1 and 2, respectively. Theprocessing device 140 may continue to process the second scanning datasets between 600-1000, and reconstruct a phase image of the target phase2 until the second scanning data set 800 is processed.

In some embodiments, the image reconstruction algorithm may include anAziRebin algorithm, a RadialRebin algorithm, a QSRebin algorithm, afiltering algorithm, an iterative reconstruction algorithm (e.g., astatistical reconstruction algorithm), a Fourier slice theoremalgorithm, a fan beam reconstruction algorithm, an analyticalreconstruction algorithm (e.g., a filtered back projection (FBP)algorithm), an algebraic reconstruction technology (ART), a simultaneousalgebraic reconstruction technology (SART), a Feldkamp-Davis-Kress (FDK)reconstruction algorithm, or the like, or any combination thereof. Insome embodiments, the processing device 140 may post-process thereconstructed phase images using a post-processing algorithm. In someembodiments, the post-processing algorithm may include a Ringoffalgorithm, a TV algorithm, an MPR algorithm, or the like, or anycombination thereof.

In 730, the processing device 140 (e.g., the reconstruction module 840)may determine whether an image output number is greater than 0; that is,whether a phase image is generated.

In response to determining that the image output number is greater than0, the processing device 140 may proceed to perform operation 740. Inresponse to determining that the image output number does not greaterthan 0, the processing device 140 may return to perform operation 710.

In 740, the processing device 140 (e.g., the reconstruction module 840)may store a phase image of a target phase into a second storage device.In some embodiments, the first storage device and the storage device maybe the same or different. For example, the first storage device and thesecond storage device may be integrated into one specific storagedevice.

In 750, the processing device 140 (e.g., the reconstruction module 840)may determine whether the second scanning data set is the last one ofthe plurality of second scanning data sets of the second time period.

In response to determining that the second scanning data set is not thelast one of the plurality of second scanning data sets, the processingdevice 140 may proceed to perform operation 710. In response todetermining that the second scanning data set is the last one of theplurality of second scanning data sets, the processing device 140 mayterminate the image reconstruction process, and output the phase imagesof the scanning object stored in the second storage device.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

In some embodiments, the processing device 140 may retrieve once, frommultiple scanning data sets of a scanning process of the scanningobject, the plurality of second scanning data sets for reconstructingthe phase images each of which corresponds to a target phase. Theprocessing device 140 may pre-process once the retrieved second scanningdata sets. For example, as shown in FIG. 9C, [S1, E3] represents asecond time period of a target motion cycle. The processing device 140may acquire the second scanning data sets for reconstructing the phaseimages of the scanning object by a single retrieval. That is, theprocessing device 140 may directly retrieve the second scanning datasets acquired during [S1, E3] of the target motion cycle. It should benoted that the second scanning data sets of each of one or more targetmotion cycles may be retrieved and/or pre-processed simultaneously orsequentially. For example, the processing device 140 may first retrieveand/or pre-process the second scanning data sets acquired during asecond time period of a first target motion cycle, and then retrieveand/or pre-process the second scanning data sets acquired during asecond time period of a target second motion cycle. As another example,the processing device 140 may simultaneously retrieve and/or pre-processthe second scanning data sets of the one or more target motion cycles.As a further example, the processing device 140 may first retrieveand/or pre-process the second scanning data sets acquired during [S1,S3] of the one or more target motion cycles, then retrieve and/orpre-process the second scanning data sets acquired during [S3, E1] ofthe one or more target motion cycles, and finally retrieve and/orpre-process the reset second scanning data sets acquired during [E1, E3]of the one or more target motion cycles.

FIG. 8 is a block diagram of an exemplary processing device according tosome embodiments of the present disclosure. The processing device 140may determine second scanning data sets corresponding to multiple targetphases, and retrieve once the second scanning data sets from multiplescanning data sets acquired during a scanning process. As shown in FIG.8 , the processing device 140 may include an acquisition module 810, adetermination module 820, a retrieval module 830, and a reconstructionmodule 840.

The acquisition module 810 may be configured to obtain information/dataassociated with image reconstruction of at least two target phases. Forexample, the acquisition module 810 may obtain the target phases fromone or more component of the data processing system 100. As anotherexample, the acquisition module 810 may obtain scanning data acquiredduring a scanning process.

The determination module 820 may be configured to identify at least twofirst time periods during the scanning process, each of the at least twofirst time periods corresponding to one of the at least two targetphases. The determination module 820 may further be configured todetermine a second time period that encloses the at least two first timeperiods. In some embodiments, the determination module 820 may identifya starting time point and an ending time point of a target motion cycleof the motion. For each of the at least two target phases, thedetermination module 820 may identify, based on the target phase, thestarting time point of the target motion cycle, and the ending timepoint of the target motion cycle, a preset time point corresponding tothe target phase. The determination module 820 may determine a targetdata acquisition time point corresponding to the target phase based onthe preset time point, and determine, based on the target dataacquisition time point, the first period corresponding to the targetphase. In some embodiments, the determination module 820 may identify astarting time point and an ending time point for each of the at leasttwo first time periods. The determination module 820 may designate anearlier starting time point of the at least two starting time points ofthe at least two first time periods as a starting time point of thesecond time period, and designate a later ending time point of the atleast two ending time points of the at least two first time periods asan ending time point of the second time period.

The retrieval module 830 may be configured to retrieve scanning data. Insome embodiments, the retrieval module 830 may retrieve once, from themultiple scanning data sets, corresponding scanning data sets forreconstructing phase images each of which corresponds to one targetphase.

The reconstruction module 840 may be configured to reconstruct one ormore images based on scanning data. In some embodiments, thereconstruction module 840 may pre-process the scanning data, andgenerate phase images based on the pre-processed scanning data. In someembodiments, for each target phase, the reconstruction module 840 mayidentify, from the pre-processed scanning data, pre-processed scanningdata sets of the target phase. The reconstruction module 840 mayreconstruct, based on the pre-processed scanning data sets correspondingto the target phase, a phase image of the target phase. In someembodiments, the reconstruction module 840 may post-process the phaseimages.

The modules in the processing device 140 may be connected to orcommunicate with each other via a wired connection or a wirelessconnection. The wired connection may include a metal cable, an opticalcable, a hybrid cable, or the like, or any combination thereof. Thewireless connection may include a Local Area Network (LAN), a Wide AreaNetwork (WAN), a Bluetooth, a ZigBee, a Near Field Communication (NFC),or the like, or any combination thereof. Two or more of the modules maybe combined as a single module, and any one of the modules may bedivided into two or more units. For example, the processing device 140may further include a storage module (not shown in FIG. 8 ). The storagemodule may be configured to store data generated during any processperformed by any component of in the processing device 140. As anotherexample, each of the components of the processing device 140 may includea storage device. Additionally or alternatively, the components of theprocessing device 140 may share a common storage device.

FIG. 10 is a flowchart illustrating an exemplary single-phase imagereconstruction mode according to some embodiments of the presentdisclosure. As shown in FIG. 10 , the process 1000 (e.g., a process ofimage reconstruction of CT scan) may include acquiring scanning data1010, retrieving reconstruction data 1015, pre-processing reconstructiondata 1020, reconstructing a phase image 1025, image fusion 1030,post-processing the reconstructed phase image 1035, and storing thepost-processed phase image 1040.

The acquiring scanning data 1010 refers to obtaining scanning data froma storage device. The retrieving reconstruction data 1015 may includeselecting the reconstruction data for reconstructing an image of a phasebased on a target phase, and retrieve the selected scanning data. Thepre-processing of reconstruction data 1020 refers to pre-processing theretrieved reconstruction data using a pre-processing algorithm. In someembodiments, the pre-processing algorithm may include an air calibrationalgorithm, an inter-layer normalization algorithm, a crosstalkcorrection algorithm, a nonlinear correction algorithm, a CT valuecalibration (HU) algorithm, a bad channel correction algorithm, a beamhardening correction algorithm, or the like, or any combination thereof.The reconstructing a phase image 1025 refers to generating a phase imageof the scanned object based on the pre-processed reconstruction datausing an image reconstruction algorithm. In some embodiments, the imagereconstruction algorithm may include an AziRebin algorithm, aRadialRebin algorithm, a QSRebin algorithm, a filtering algorithm, aniterative reconstruction algorithm (e.g., a statistical reconstructionalgorithm), a Fourier slice theorem algorithm, a fan beam reconstructionalgorithm, an analytical reconstruction algorithm (e.g., a filtered backprojection (FBP) algorithm), an algebraic reconstruction technology(ART), a simultaneous algebraic reconstruction technology (SART), aFeldkamp-Davis-Kress (FDK) reconstruction algorithm, or the like, or anycombination thereof. The image fusion 1030 may include first fusing twosets of sequence images (i.e., the BP(FS)) generated by a full scanalgorithm, and then fusing sequence images (i.e., the BP(PS)) generatedby the partial scan algorithm and the fused image to generate areconstructed image. The post-processing the reconstructed image 1035refers to post-processing the reconstructed image using apost-processing algorithm to improve the quality (e.g., contrast,clarity) of the reconstructed image. In some embodiments, thepost-processing algorithm may include a Ringoff algorithm, a TValgorithm, an MPR algorithm, or the like, or any combination thereof.The storing the post-processed phase image 1040 may include transmittingthe post-processed reconstructed image to a storage device for storage.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by this disclosure and arewithin the spirit and scope of the exemplary embodiments of thisdisclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “module,” “unit,” “component,” “device,” or “system.”Furthermore, aspects of the present disclosure may take the form of acomputer program product embodied in one or more computer readable mediahaving computer readable program code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET,Python or the like, conventional procedural programming languages, suchas the “C” programming language, Visual Basic, Fortran 2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages such as Python, Ruby, andGroovy, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose and that the appended claimsare not limited to the disclosed embodiments, but, on the contrary, areintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the disclosed embodiments. For example,although the implementation of various components described above may beembodied in a hardware device, it may also be implemented as a softwareonly solution, e.g., an installation on an existing server or mobiledevice.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various embodiments. This method ofdisclosure, however, is not to be interpreted as reflecting an intentionthat the claimed subject matter requires more features than areexpressly recited in each claim. Rather, claim subject matter lie inless than all features of a single foregoing disclosed embodiment.

What is claimed is:
 1. A system, comprising: at least one storage devicestoring executable instructions for reconstructing phase images, and atleast one processor in communication with the at least one storagedevice, wherein when executing the executable instructions, the at leastone processor is configured to cause the system to perform operationsincluding: acquiring, in a scanning process, at least two target phasesof a motion of a scanning object, wherein the scanning process involvesmultiple data acquisition time points each of which corresponds to ascanning data set; obtaining, from the multiple scanning data sets, aplurality of second scanning data sets acquired at second dataacquisition time points of the multiple data acquisition time pointswithin a first time period; pre-processing once the second scanning datasets; and reconstructing, based on the pre-processed second scanningdata sets, phase images each of which corresponds to one of the at leasttwo target phases.
 2. The system of claim 1, wherein the reconstructing,based on the pre-processed second scanning data sets, the phase imagesincludes: for each of the at least two target phases; identifying, fromthe pre-processed second scanning data sets, pre-processed secondscanning data sets of the target phase; and reconstructing, based on thepre-processed second scanning data sets corresponding to the targetphase, a phase image of the target phase.
 3. The system of claim 2,wherein each of the pre-processed second scanning data sets of thetarget phase corresponds to a data acquisition angle, and the dataacquisition angles of the pre-processed second scanning data sets of thetarget phase are with a first angle range corresponding to the targetphase.
 4. The system of claim 1, further comprising: for each of thesecond scanning data set, identifying, to which of the at least twotarget phases, a second data acquisition time point corresponding to thesecond scanning data set corresponds.
 5. The system of claim 4, whereinthe identifying, to which of the at least two target phases, the seconddata acquisition time point corresponding to the second scanning dataset corresponds includes identifying, to which of second time periods,the second data acquisition time point belongs.
 6. The system of claim5, wherein the second time periods are identified during the scanningprocess, each of the second time periods corresponding to one of the atleast two target phases, and the first time period encloses the secondtime periods.
 7. The system of claim 4, wherein the identifying, towhich of the at least two target phases, the second data acquisitiontime point corresponding to the second scanning data set corresponds isbased on a data acquisition angle corresponding to each second scanningdata set.
 8. The system of claim 1, further comprising: for each of thesecond scanning data set, determining whether the second scanning dataset satisfies a compliance condition; in response to determining thatthe second scanning data set satisfies the compliance condition,reconstructing a phase image based on the second scanning data set. 9.The system of claim 8, wherein the determining whether the secondscanning data set satisfies the compliance condition includes:determining whether an index of the second scanning data set exceeds anindex threshold.
 10. The system of claim 1, further comprising:identifying at least two second time periods during the scanningprocess, each of the at least two second time periods corresponding toone of the at least two target phases; and determining the first timeperiod that encloses the at least two second time periods.
 11. Thesystem of claim 10, wherein the identifying at least two second timeperiods includes: identifying a starting time point and an ending timepoint of a motion cycle of the motion; for each of the at least twotarget phases, identifying, based on the target phase, the starting timepoint of the motion cycle, and the ending time point of the motioncycle, a preset time point corresponding to the target phase;determining, based on the preset time point, a target data acquisitiontime point corresponding to the target phase; and determining, based onthe target data acquisition time point, the second time periodcorresponding to the target phase.
 12. The system of claim 11, whereinthe at least two second time periods both fall within a range within themotion cycle.
 13. The system of claim 11, wherein the determining, basedon the target data acquisition time point, the second time periodcorresponding to the target phase includes: determining a target dataacquisition angle at the target data acquisition time pointcorresponding to the target phase; determining a first angle rangecentering at the target data acquisition angle corresponding to thetarget phase; and designating, as the second time period, a plurality ofdata acquisition time points each of which corresponds to a dataacquisition angle within the first angle range.
 14. The system of claim10, wherein the determining the first time period that encloses the atleast two second time periods includes: identifying a starting timepoint and an ending time point for each of the at least two second timeperiods; designating an earlier starting time point of the at least twostarting time points of the at least two second time periods as astarting time point of the first time period; and designating a laterending time point of the at least two ending time points of the at leasttwo second time periods as an ending time point of the first timeperiod.
 15. A method implemented on a computing device including atleast one processor and at least one storage medium, and a communicationplatform connected to a network, the method comprising: acquiring, in ascanning process, at least two target phases of a motion of a scanningobject, wherein the scanning process involves multiple data acquisitiontime points each of which corresponds to a scanning data set; obtaining,from the multiple scanning data sets, a plurality of second scanningdata sets acquired at second data acquisition time points of themultiple data acquisition time points within a first time period;pre-processing once the second scanning data sets; and reconstructing,based on the pre-processed second scanning data sets, phase images eachof which corresponds to one of the at least two target phases.
 16. Themethod of claim 15, wherein the reconstructing, based on thepre-processed second scanning data sets, the phase images includes: foreach of the at least two target phases; identifying, from thepre-processed second scanning data sets, pre-processed second scanningdata sets of the target phase; and reconstructing, based on thepre-processed second scanning data sets corresponding to the targetphase, a phase image of the target phase.
 17. The method of claim 16,wherein each of the pre-processed second scanning data sets of thetarget phase corresponds to a data acquisition angle, and the dataacquisition angles of the pre-processed second scanning data sets of thetarget phase are with a first angle range corresponding to the targetphase.
 18. The method of claim 15, further comprising: for each of thesecond scanning data set, identifying, to which of the at least twotarget phases, a second data acquisition time point corresponding to thesecond scanning data set corresponds.
 19. The method of claim 18,further comprising: for each of the second scanning data set,determining whether the second scanning data set satisfies a compliancecondition; in response to determining that the second scanning data setsatisfies the compliance condition, reconstructing a phase image basedon the second scanning data set.
 20. A non-transitory computer readablemedium, comprising at least one set of instructions for scanning dataprocessing, wherein when executed by one or more processors of acomputing device, the at least one set of instructions causes thecomputing device to perform a method, the method comprising: acquiring,in a scanning process, at least two target phases of a motion of ascanning object, wherein the scanning process involves multiple dataacquisition time points each of which corresponds to a scanning dataset; obtaining, from the multiple scanning data sets, a plurality ofsecond scanning data sets acquired at second data acquisition timepoints of the multiple data acquisition time points within a first timeperiod; pre-processing once the second scanning data sets; andreconstructing, based on the pre-processed second scanning data sets,phase images each of which corresponds to one of the at least two targetphases.